Collaborative Optimization Of Passenger Flow Control And Train Timetable For Urban Rail Transit

With the continuous expansion of the urban rail transit network and the continuous increase of travel demand,the congestion situation in stations and trains of the urban rail transit system is becoming increasingly prominent,especially during the morning and evening peak periods.Passenger congestion has become a key factor restricting the sustainable development of urban rail transit.It will not only seriously affect travel satisfaction and service quality,but also pose an important threat to the personal safety of passengers and the efficient operation of trains.Passenger flow control and train timetable optimization,as two effective approaches to managing passenger flow and vehicle operation respectively,have attracted extensive attention of scholars and traffic managers.However,most of the previous studies focused on passenger flow management and timetable optimization respectively,and lacked relevant content on collaborative optimization of passenger flow control strategy and timetable.Moreover,the theoretical research on multi-station and refined passenger flow management and control is also insufficient.In this regard,based on the over-saturated conditions and the actual passenger flow data of urban rail transit,aiming at ensuring passenger travel safety and efficient train operation,this paper put forward some methods and optimization models.For example,a data-driven calculation method of passenger flow control intensity from the perspective of the imbalance between passenger flow demand and the supply of equipment of rail transit system,the optimization model of multi-station collaborative passenger flow control measures,and the collaborative optimization models of passenger flow control and train timetable are constructed.The specific research contents include:(1)Research on the travel characteristics and calculation method of passenger flow control intensity based on data.Thanks to the universal of the Automatic Fare Collection System(AFC),a large number of passenger travel data can be collected by swiping cards when passengers get in/out of the stations.Taking Beijing Urban Rail Transit as an example,based on the rich passenger travel characteristics and information contained in AFC data,this paper analyzes the macro and mesoscopic distribution of passengers from two dimensions of space and time.Further,considering the three indicators of inbound,outbound and transfer passenger flow,a data-driven calculation method of passenger flow control intensity is proposed.Based on the Beijing Urban Rail Transit network,the rationality and feasibility of this method are verified and analyzed.The results show that the obtained bus station flow control intensity is in line with the actual situation,and can reflect the characteristics of demand and station.(2)Optimization of passenger flow control strategy for the urban rail transit network.First,the travel time distribution of urban rail transit passenger flow demand is analyzed by using AFC data.Then an optimization model of network-level passenger flow control strategy is constructed considering the capacity constraints of infrastructure equipment and flow control requirements.The goal of the proposed model is to minimize the passenger delay time outside the stations and on the platforms.Finally,taking Lines 1,2,and 5 of Beijing Urban Rail Transit as examples,the effectiveness of the model is verified.The results show that the optimized passenger flow control strategy can effectively reduce the number of waiting passengers.(3)Collaborative optimization of passenger flow control and train timetable for urban rail transit.Based on the oversaturation of urban rail transit and the headwaydependent passenger flow demand,the interaction relationship between passenger flow and train flow,and the mutual restriction relationship between passenger demand and system capacity are comprehensively analyzed.Aiming at minimizing the number of stranded passengers outside the stations and on the platforms,the collaborative optimization model of passenger flow control and timetable is constructed.Line 5 of Beijing Urban Rail Transit is adopted as an example.The results show that the collaborative model can optimize the passenger flow control strategy and timetable at the same time.Moreover,the proposed optimization method can effectively improve the average boarding rate and reduce passenger delays.(4)An integrated optimization approach for passenger flow control strategy and metro train scheduling considering skip-stop patterns.First,based on the different skipstop modes and the requirements of different train load factors,the interaction and influence relationship between passengers and trains in peak hours is analyzed.A mixed integer linear programming model of passenger flow control and train timetable is formulated to minimize the wasted capacity of trains and the total number of waiting passengers at platforms and outside stations.A case study is tested in Beijing Urban Rail Transit Line 1 to illustrate the validity of the proposed method.In addition,a discussion and comparison of the performance of integration optimization strategies with diverse scenarios are given.The results show that the average travel time and the number of stranded passengers outside the station and platform are reduced under the optimized combination strategy,and the average boarding rate of each station is improved.(5)Coordinated optimization of passenger flow control strategy and full-length and short-turn plan for trains in urban rail transit.A peak period of urban rail transit is selected to research this joint issue based on the flexible combined operation mode of full-length and short-turn.Aiming at minimizing the number of stranded passengers outside the station and platform,train operation distance and time,a multi-objective optimization model with nonlinear constraints is proposed.Besides,this problem is equivalently converted to a single-objective mixed integer programming model through the minimummaximum method,linear weighting method and reasonable linearization method.Then,to verify the primal problem,Beijing Urban Rail Transit Line 5 is taken.It is found that a complete set of passenger flow control strategies and full-length and short-turning operation schemes for trains can be obtained simultaneously using this optimization model.In addition,the results show that the total operation distance and total running time are greatly reduced.This thesis contains a total of 72 figures,33 tables,and 150 references.